%load_ext autoreload
%autoreload 2
from import_src import *

from collections import OrderedDict

# TODO: import the portfolio for a single source

large_us_stocks = OrderedDict({
    "VTI": 0.8,
    "VNQ (REIT)": 0.2
})

large_exus_stocks = OrderedDict({
    "EAFE": 1.
})

small_us_stocks = OrderedDict({
    "IJS": 1.
})

small_exus_stocks = OrderedDict({
    "EAFE Small-Cap": 1.
})

bonds = OrderedDict({
    "BND": 1.
})

fund_shares = [large_us_stocks, large_exus_stocks, small_us_stocks, small_exus_stocks, bonds]

Variate portfolio by Stock/Bond ratio

from src.domain import *
from src.distribution import create_distributions_from
from src.display.distribution import display_distributions

default_distribution = SharesDistribution(
    categories=SharesCategoriesDistribution(
        by_type=dict(zip((ShareType.Stock, ShareType.Bond), (0.75, 0.25))),
        by_region=dict(zip((Region.US, Region.ExUS), (0.7, 0.3))),
        by_cap=dict(zip((Cap.Large, Cap.Small), (0.7, 0.3))),
        by_term=dict(zip((Term.Long, ), (1, ))),
    ),
    shares=[FundsDistribution(x) for x in fund_shares]
)

def modify_distrib_by_type_ratio(distrib: SharesDistribution, stock_rate: float):
    if distrib.categories:
        bond_rate = 1 - stock_rate
        distrib.categories.by_type[ShareType.Stock] = stock_rate
        distrib.categories.by_type[ShareType.Bond] = bond_rate

distributions_rates = [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1]
distributions_names = [f'{round(x * 100)}/{round((1 - x) * 100)}' for x in distributions_rates]
distributions = create_distributions_from(default_distribution, modify_distrib_by_type_ratio, distributions_rates)

display_distributions(distributions, names=distributions_names)

	0/100	10/90	20/80	30/70	40/60	50/50	60/40	70/30	80/20	90/10	100/0
VTI	0.0%	3.92%	7.84%	11.76%	15.68%	19.6%	23.52%	27.44%	31.36%	35.28%	39.2%
VNQ (REIT)	0.0%	0.98%	1.96%	2.94%	3.92%	4.9%	5.88%	6.86%	7.84%	8.82%	9.8%
EAFE	0.0%	2.1%	4.2%	6.3%	8.4%	10.5%	12.6%	14.7%	16.8%	18.9%	21.0%
IJS	0.0%	2.1%	4.2%	6.3%	8.4%	10.5%	12.6%	14.7%	16.8%	18.9%	21.0%
EAFE Small-Cap	0.0%	0.9%	1.8%	2.7%	3.6%	4.5%	5.4%	6.3%	7.2%	8.1%	9.0%
BND	100.0%	90.0%	80.0%	70.0%	60.0%	50.0%	40.0%	30.0%	20.0%	10.0%	0.0%

	Mean ret.	Std
0/100	5.12	3.69
10/90	5.69	3.71
20/80	6.24	4.29
30/70	6.77	5.25
40/60	7.27	6.41
50/50	7.76	7.70
60/40	8.22	9.04
70/30	8.66	10.43
80/20	9.08	11.85
90/10	9.47	13.28
100/0	9.84	14.72

Variate portfolio by Cap size ratio

from src.domain import *
from src.distribution import create_distributions_from
from src.display.distribution import display_distributions

default_distribution = SharesDistribution(
    categories=SharesCategoriesDistribution(
        by_type=dict(zip((ShareType.Stock, ShareType.Bond), (1, 0))),
        by_region=dict(zip((Region.US, Region.ExUS), (0.7, 0.3))),
        by_cap=dict(zip((Cap.Large, Cap.Small), (0.7, 0.3))),
        by_term=dict(zip((Term.Long, ), (1, ))),
    ),
    shares=[FundsDistribution(x) for x in fund_shares]
)

def modify_distrib_by_cap_ratio(distrib: SharesDistribution, large_cap: float):
    if distrib.categories:
        small_cap = 1 - large_cap
        distrib.categories.by_cap[Cap.Large] = large_cap
        distrib.categories.by_cap[Cap.Small] = small_cap

distributions_rates = [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1]
distributions_names = [f'{round(x * 100)}/{round((1 - x) * 100)}' for x in distributions_rates]
distributions = create_distributions_from(default_distribution, modify_distrib_by_cap_ratio, distributions_rates)

display_distributions(distributions, names=distributions_names)

	0/100	10/90	20/80	30/70	40/60	50/50	60/40	70/30	80/20	90/10	100/0
VTI	0.0%	5.6%	11.2%	16.8%	22.4%	28.0%	33.6%	39.2%	44.8%	50.4%	56.0%
VNQ (REIT)	0.0%	1.4%	2.8%	4.2%	5.6%	7.0%	8.4%	9.8%	11.2%	12.6%	14.0%
EAFE	0.0%	3.0%	6.0%	9.0%	12.0%	15.0%	18.0%	21.0%	24.0%	27.0%	30.0%
IJS	70.0%	63.0%	56.0%	49.0%	42.0%	35.0%	28.0%	21.0%	14.0%	7.0%	0.0%
EAFE Small-Cap	30.0%	27.0%	24.0%	21.0%	18.0%	15.0%	12.0%	9.0%	6.0%	3.0%	0.0%
BND	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%

	Mean ret.	Std
0/100	10.96	16.83
10/90	10.82	16.45
20/80	10.67	16.09
30/70	10.52	15.76
40/60	10.35	15.46
50/50	10.19	15.18
60/40	10.01	14.94
70/30	9.84	14.72
80/20	9.65	14.55
90/10	9.46	14.40
100/0	9.27	14.30

Variate portfolio by Region ratio

from src.domain import *
from src.distribution import create_distributions_from
from src.display.distribution import display_distributions

default_distribution = SharesDistribution(
    categories=SharesCategoriesDistribution(
        by_type=dict(zip((ShareType.Stock, ShareType.Bond), (1, 0))),
        by_region=dict(zip((Region.US, Region.ExUS), (0.7, 0.3))),
        by_cap=dict(zip((Cap.Large, Cap.Small), (0.7, 0.3))),
        by_term=dict(zip((Term.Long, ), (1, ))),
    ),
    shares=[FundsDistribution(x) for x in fund_shares]
)

def modify_distrib_by_region_ratio(distrib: SharesDistribution, us_rate: float):
    if distrib.categories:
        exUs_rate = 1 - us_rate
        distrib.categories.by_region[Region.US] = us_rate
        distrib.categories.by_region[Region.ExUS] = exUs_rate

distributions_rates = [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1]
distributions_names = [f'{round(x * 100)}/{round((1 - x) * 100)}' for x in distributions_rates]
distributions = create_distributions_from(default_distribution, modify_distrib_by_region_ratio, distributions_rates)

display_distributions(distributions, names=distributions_names)

	0/100	10/90	20/80	30/70	40/60	50/50	60/40	70/30	80/20	90/10	100/0
VTI	0.0%	5.6%	11.2%	16.8%	22.4%	28.0%	33.6%	39.2%	44.8%	50.4%	56.0%
VNQ (REIT)	0.0%	1.4%	2.8%	4.2%	5.6%	7.0%	8.4%	9.8%	11.2%	12.6%	14.0%
EAFE	70.0%	63.0%	56.0%	49.0%	42.0%	35.0%	28.0%	21.0%	14.0%	7.0%	0.0%
IJS	0.0%	3.0%	6.0%	9.0%	12.0%	15.0%	18.0%	21.0%	24.0%	27.0%	30.0%
EAFE Small-Cap	30.0%	27.0%	24.0%	21.0%	18.0%	15.0%	12.0%	9.0%	6.0%	3.0%	0.0%
BND	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%

	Mean ret.	Std
0/100	6.17	15.87
10/90	6.72	15.53
20/80	7.26	15.25
30/70	7.79	15.02
40/60	8.31	14.85
50/50	8.83	14.74
60/40	9.34	14.70
70/30	9.84	14.72
80/20	10.33	14.81
90/10	10.81	14.96
100/0	11.29	15.17